Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use henryscheible/eval_v2_mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/eval_v2_mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/eval_v2_mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/eval_v2_mrpc") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/eval_v2_mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download test_results.json from henryscheible/eval_v2_mrpc: direct link, hf CLI and curl.
- Browser
- Download file 134 Bytes
-
https://huggingface.co/henryscheible/eval_v2_mrpc/resolve/main/test_results.json
- Command line
-
hf download hf://henryscheible/eval_v2_mrpc/test_results.json
-
curl -L -o test_results.json https://huggingface.co/henryscheible/eval_v2_mrpc/resolve/main/test_results.json
134 Bytes
| { | |
| "eval_runtime": 14.4617, | |
| "eval_samples": 1725, | |
| "eval_samples_per_second": 119.281, | |
| "eval_steps_per_second": 14.936 | |
| } |